Industry 4.0 holds the promise of helping organizations in manufacturing, transportation, energy, and urban development to digitally transform with IoT-enabled technologies, advanced analytics, artificial intelligence (AI) and machine learning (ML). Underlying these digital technologies are assets providing vast amounts of data through an array of sensors and IoT-connected assets. And the number of IoT-connected assets is expanding at an unprecedented rate, with industry analysts anticipating 20–30 billion IoT-connected assets by 2020. As assets and sensors multiply, the data coming from each asset is exploding in volume and velocity, making the management of that data difficult.

In addition, teams within organizations often have siloed access to data, making management inefficient, and creating incomplete pictures of the health of assets and the entire company. Poor information management contributes to costly unscheduled machine breakdowns, and impacts your bottom line.

To reduce the risk of downtime and make asset management more efficient, organizations need a way to break down data silos, get more insight into their assets, and put information in the hands of the people who need it—when they need it. Asset avatars were designed to provide a 360-degree view of assets, and deliver this information to decision makers across the organization.

An asset avatar is a digital representation of a physical asset. It enables you to view and monitor key performance indicators (KPIs) – such as an asset's sensors, current and historical state, properties and events – no matter where these assets are geographically located. Asset avatars and the assets they represent have a 1:1 relationship – meaning that a single asset avatar is associated with only one asset. Asset avatars integrate data from many different locations to enable better information management, collaboration and lower operational costs.

Asset avatars are also defined by an asset avatar type, which is a digital blueprint for a class of physical assets of the same type. The asset avatar type enriches your asset avatar with information about your asset's identity. Asset avatar types can also be associated with assets and applied to asset avatars that share the same characteristics. When it comes to mapping, asset avatar types help translate your asset's raw, unintelligible data to easily understood information.

By providing a 360-degree view of your assets, along with seamless integration to your business systems, asset avatars deliver benefits across the organization. For example, bringing information together in new and meaningful ways with ML and AI can help you to predict and prevent failure of assets, reducing costly unplanned downtime.

With this information, you can also extend the useful life of the machines that run your business by predicting when maintenance is needed and automatically scheduling it when the data dictates, further reducing downtime.

Video according to some is the new killer app. The reason? It’s more than right place, right time. Video is the lifeblood of nearly every next big thing, from augmented reality (AR) and virtual reality (VR) to how business happens and how lives are impacted. On a small scale, let’s take my recent installation of Ring’s home security system, which starts with a video connected doorbell and extends to a base station, sensors and other smart home devices. If someone rings my doorbell at home, I can reply via real-time video communication from inside my home office or wherever I’m at in the moment—even another country. It was really simple to install and customize—an easy way to provide my family with a modern-day neighborhood watch.

On an enterprise scale, modern video applicability is widespread across industries and has become a transformational medium for government and commercial use cases. An easy example is the drone, which has morphed from a fun-to-own, annoying-to-neighbors gadget to an economically viable, business-critical tool capable of gauging, testing, guiding, instructing, forecasting, delivering, installing, repairing and inspecting whatever.

So, what does it mean for the telco and communications industry? Some carriers might answer by saying that they’re laser-focused on investing in the right technologies to monetize network investments.

Monetizing the right set of video capabilities means being able to offer next-gen choice and expanded coverage to customers. Industries where video can boost productivity, create new market share, protect consumers and workers — they’re looking for innovative ways to deliver new solutions. Enterprises within these industries are going to: A) find a telco partner to provide the video bandwidth capabilities (and surrounding services); B) partner with a telco or communications company to build it; or C) build it themselves.

Smack in the middle of the hype-to-naysayer spectrum lie the economics and opportunities for telcos to adopt and capitalize on video capabilities. For telcos investing heavily on new network fiber rollouts, with bigger pipes preparing the network for 5G or telcos teetering on the precipice of investment, now’s the time to quell bandwidth-hungry applications. Now’s the time to put in place the network capacity that will enable the Telco’s to create new services and solutions to monetize network investments going forward.

Hitachi Vantara is delivering a double bottom line for telcos: pairing must-have technologies that support the killer app ecosystem with must-do societal business outcomes that benefit the world we all live in. Our smart spaces initiatives and intelligent video technologies are making a difference.

Click the link below and watch the Smart Spaces and Video Intelligence 'video' to see how Hitachi Vantara is making a difference.

I continue to get excited when we’re innovative and passionate about what can be achieved. Here at Hitachi Vantara, we’ve been working with so many doers to optimize video offerings, scale backend IoT connectivity and reach desired economics.

Which brings us back to the idea of relevancy for telcos. The idea starts with smart devices or assets connected to other smart devices, which are then connected inside a system of smart things. That smart system is connected to other smart systems and so on. The possibilities are endless. Video is wearing the crown of smart.

Next time, let's talk about the royal treatment, a.k.a. customer experience.

What are your immediate business objectives? I don’t like second guessing but here are some scenarios where Industrial Internet of things (IIoT) can make a significant difference:

>Are you stuck in a me-too industry and are looking for a competitive advantage to give you an edge in the marketplace?

>Do you desire improved productivity from your assets and people?

> Do you have blind spots in your operations?

>Do you want to explore new business models that support new revenue opportunities?

>Do you want to move from products to as a services customer engagement models?

>Or do you want to improve your product quality and customer experience?

If one or more of these scenarios resonate with your business needs, then it is time to consider implementing IoT solutions to help you in this journey from edge to outcomes.

IoT might sound futuristic, but the technology itself has existed for a long time. Machine-to-machine networks and control systems, data analytics, remote tracking and guidance systems, enterprise applications etc have been aggregated into an IoT Technology Stack to provide a unified view of operations and control.

IoT has proven to contribute to similar outcomes such as:

New business models generating new revenue

Remote asset monitoring enabling costs savings

Improved processes leading to higher yield and reduced wastage

Hidden and Dark Data Leading to new Insights and accelerated innovation

As per a recent Forbes study, 66% of successful companies include external vendors on their IoT Planning team. It would be of tremendous value to have an experienced co-creation partner to support with leading practices.

The explosive growth of IoT isn’t hypothetical; it’s happening today in every sector. Digital transformation is here, and while it is changing industries in new ways, that change doesn’t always come easy. Challenges abound, and when it comes to edge computing, companies are finding some common concerns, including:

· Latency: Cloud computing is becoming more powerful by the day, but some use cases require data to be processed within milliseconds. Sending data to a backend system, whether it’s located in a public cloud, private cloud or data center, introduces too much latency for these use cases.

· Perishable data: Not all data is useful in the data center. Sometimes data needs to be acted upon right away with low latency. Perishable data, like the data generated by autonomous vehicles, can’t wait until tomorrow. It must be analyzed at the edge for immediate action.

· Limited bandwidth: Bandwidth at the edge is often limited, so deciding what data to send can be difficult. Sending everything back to the data center is expensive, time consuming and inefficient. To make the best use of resources and to save time and money, it’s essential to prioritize data and send only what you need.

· Uninteresting data: Assets and sensors generate huge volumes of data, but not all of it matters to you. You might want to know when an asset is operating outside of normal parameters, but perhaps you don’t need to capture, store, transmit, and analyze the data that’s generated when it’s operating normally. You might also want to reduce the amount of data collected to relieve the burden and overhead of data management.

· Security: Bringing assets onto the network puts them at risk of being infected with malware. With the growth in smart assets and the fact that cyber attacks are escalating in number and sophistication, securing assets and protecting the integrity of the data and network is vital.

Across every industry, analytics and business intelligence are hot topics that promise greater insight, more efficiency, and a more competitive organization. And analytics can truly deliver on those promises, despite the myriad challenges that many organizations face in getting that value.

One of the most pervasive challenges today is siloed data. Data coming from assets may be used only at the edge, while business applications often have their own separate infrastructure, databases, and sets of information. Getting a complete picture of information across the organization is difficult—often impossible. Without the ability to bring data from disparate systems together in a way that enables fast, smart decision making, business outcomes are poor and costs are high.

Not only are data silos a common problem, but data generation itself can be a challenge, too. Many organizations have not been ready to take advantage of analytics capabilities, and don’t generate enough data to derive insights from. Other organizations may generate large volumes of data in the hope that they can derive some business value from it, but lack the filtering capabilities to make sense of data and put the right information in the hands of people who need it.

Good predictive abilities require good data gathering and filtering processes. By bringing together the right data from across the organization, whether it lives at the edge or in the data center, the results can be better business outcomes. The analytics capabilities of Lumada address these challenges and deliver fast time-to-value, so that your outcomes are better, faster.

Creating or acquiring IoT solutions can be complex and may seem daunting. Where do I start? Do I have access to all the resources and expertise that will be needed? Is there someone that can help and guide me?

If you’re used to buying pre-packaged solutions for specific tasks, then you are likely to discover that these can’t deliver what you want or need in IoT. It's unchartered territory for many.

IoT solutions most often combine the physical and digital worlds, almost by definition. They connect to your physical environment – your Operational Technology (OT) – your machines, your buildings, your sensors, etc. They also connect with your IT environment – your ERP system, your CRM system, your procurement system, etc. A successful solution creation and deployment takes expertise in multiple disciplines and deep knowledge about your OT and IT environments as well as the business challenges you’re trying to address. Very few companies have that breadth of expertise in one team or even inside one company. Hitachi does, and we’ve made it our business to help other companies with this.

This is where the Co-Creation methodology we use comes in. It’s a methodology we have proven in real life with customers and also inside Hitachi itself. Hitachi has both the OT and IT expertise and capabilities in the Hitachi Group. We’re not only creating IoT solutions – we have first hand experience from running factories, hospitals, transportation services, etc. So we're both a technology and solution provider as well as a user of these solutions. It's very unique to have this dual perspective.

We recently worked with 451 Research around research into how Co-Creation methodologies and the associated services are used in the industry. On our Hitachi Vantara web page for Co-Creation Services , we recently published both a report from 451 Research as well as several videos where Greg Knieriemen from Hitachi Vantara interviews Christian Renaud (@xianrenaud) from 451 Research and John Murphy from Hitachi Vantara about the findings in the report and what we’re seeing in our interactions with customers today.

With software and adjacent technologies continuing to eat the world, we see the pace of digital transformation accelerating in 2018 as organizations strive to enhance their customer and operational intelligence.

Organizations will grapple with a variety of digital technologies and skillsets this year to become more data-driven in order to improve their agility and decision-making capabilities. As always, they’ll be looking for ways to simplify operations and get more done with less. We predict the concepts and trends listed below will light a path for organizations to show them the way forward:

Climbing the Stairway from the Edge to the Cloud

The ongoing journey to move data, apps and other digital assets from private, on-premises data centers to public clouds will continue unabated as organizations look to reduce or eliminate internal ICT functions and responsibilities. Even in the midst of cutting costs, organizations will still struggle with concerns around cloud vendor lock-in via PaaS which will benefit IaaS virtual machines, container technologies like Docker and container orchestration technologies like Kubernetes, Docker Swarm, Mesos and Marathon. Overall, Amazon AWS plus Microsoft Azure and Office365 will continue to be the biggest beneficiaries of the public cloud megatrend. Along the way, one of the stair steps that remains on-premise is something called the Fog or the Edge. If you’re familiar with how content delivery network (CDN) proxy servers around the world cache and speed the delivery of Web content to your browser, Edge gateway devices do something similar. With more and more of an organization’s compute occurring in distant, public clouds, Edge devices residing on the local network can cache, aggregate, analyze and speed up cloud content to give employees inside the office a better experience. Edge devices can also be used with the Internet of Things where they connect to machines and cache, aggregate, and analyze data locally instead of waiting for that data to be transported to a distant cloud. Since neither people nor machines are vary tolerant of too much latency, expect the adoption of Edge gateway devices and associated local storage to surge in 2018.

Enhanced Networking Inside and Out

As organizations reduce the number of digital assets and activities that take place in-house, the primary role of ICT departments will be to create and maintain fast, reliable connectivity via wired and wireless technologies. Wired networking will be “more of the same” as we push speeds forward with fiber optics and Gigabit Ethernet to shuttle employees out to the Internet. Wireless is where things get more interesting. Inside the office, organizations will continue rolling out 802.11ac Wi-Fi access points running in the 5 GHz band to deliver data and high-bandwidth content like HD video to any device. Outside, the 3GPP has officially signed off on the first 5G specification which promises to deliver greater bandwidth, lower latency, better coverage, lower battery consumption and a higher number of simultaneously connected devices. As you might imagine, it will take some time to roll out technology based on this spec so we will look to get more mileage out of 4G technologies like LTE Advanced. On the slower side of things, you have Low-Power, Wide-Area Network (LPWAN) technologies that are making great strides for certain Internet of Things use cases. The ability to create a large wireless network in places where no cellular coverage exits is compelling for organizations capable of managing such a system. If you have devices or machines that don’t send much data every day, require years of battery life, or need to send data over long distances, one of the many LPWAN technologies might be a good fit. Whether you’re inside or outside, looking for narrowband or broadband, there’s plenty of wireless choices for organizations in 2018.

Mobility for People and IoT for Machines

While the mobile device revolution has been the biggest megatrend of this new century, the torch has now been passed to the Internet of Things. When you think about it, they’re not terribly different from each other except for the endpoints. Mobile device endpoints are proxies for people and Thing endpoints refer to machines (intelligent or otherwise). They’re both sending data about themselves and other topics of interest over a network. Both interact with apps, analytics and other on-prem or cloud data sources to derive value and business intelligence. In order to regain a level of simplicity and perhaps sanity, organizations will push back against the use of multiple enterprise platforms for Mobile people and IoT machines. Additionally, many organizations will wring their hands of having to understand an alphabet soup of protocols and myriad IoT standards and revert to using the same Web and Internet standards they already understand. Just like they currently do with Mobile and the Web, organizations will insist that IoT sends and receives JSON data to and from URLs over HTTP/REST while being displayed via HTML5, secured with TLS and brought to life with JavaScript. This use of familiar, widely-used, “good enough” Web technologies will win the day over the more advanced but esoteric technologies currently employed by IoT platforms. This move to simplicity and familiarity will reduce friction and help the Internet of Things deliver value and fulfill its promise the way the Mobile, Web and the Cloud have. Expect big changes in IoT for 2018 along with a big shakeout of the hundreds of Internet of Things platform companies.

Digital Twins make Everything Digital

The rise of Digital Twins will give every organization the starting point they’re looking for to begin their Digital Transformation. A Digital Twin is essentially a digital representation of a physical object. It can be a machine, a person, a complex mechanical subsystem, a collection of machines working together on an assembly line, or even a process. These twins have attributes or properties that describe them like a person’s heart rate or a motor’s temperature or current revolutions per minute (RPM). Organizations can assign key performance indicators (KPIs) to the current values of these properties. A red heart rate KPI might be 200 whereas a green motor temperature KPI might be 200 degrees Fahrenheit. Digital Twins can exhibit behavior by executing programming language and/or analytics code against the combination of their current property values and associated KPIs. Not only does this bring everything in an organization to life, it also facilitates the running of simulations to see how things will behave when different types of data points are fed to these Digital Twins. This is definitely the most promising and exciting technology for 2018.

Security, Privacy and GDPR cause Organizations to Stumble

Unrelenting cyberattacks keep organizations in a defensive posture rather than moving forward with important digital initiatives and deployments. While we won’t cover the myriad security steps every organization must follow in order to stay ahead of individual and state-sponsored hackers, this is one of the most important functions of an ICT department. Organizational leaders who don’t take this seriously by not funding the appropriate security technology or staffing the appropriate security employee headcount do so at their own peril. Needless to say, organizations must prioritize the privacy and protection of data, people (employees and customers), and systems if they want to remain viable. To turn up the heat a bit, the European Union’s General Data Protection Regulation (GDPR) becomes enforceable on May, 25 2018. This regulation gives control back to EU citizens and residents over their personal data by strengthening data protections for all individuals within the European Union as well as the export of personal data outside the EU. Quite a few companies operating in countries across the globe play it fast-and-loose with the security and privacy of individual data without user consent. This comes to an end in May when companies can be fined up to €20 million or 4% of their global annual revenue, whichever is greater, for violating this regulation. Any company operating in the EU must obtain explicit consent for all data collected from an individual as well as reason/purpose of using and processing that data. Additionally, that user consent may be withdrawn. Many companies around the world haven’t made the necessary changes to their digital systems to be compliant with GDPR and will be in for a rude awakening in 2018. Data privacy and security matters in a big way.

Making Sense of an Avalanche of Data with Advanced Analytics

While data and analytics systems have been around for decades, the amount of data collected for analysis by organizations has increased exponentially. With a 50x growth rate from machines alone, the Internet of Things has become the newest data source for organizations to analyze. Lots of little data integrated from people, machines and business systems adds up to an overwhelming amount of Big Data to make sense of. Luckily, there are an increasing number of streaming and batch analytics systems and tools to tackle this job. Making this trend better is that most of these technologies are open source and free which helps level the playing field between small, mid-sized and large organizations with varying amounts of money to spend. Head over to Apache.org. Another interesting trend in data science is how Python has surpassed R as the most popular language for Machine Learning. An increase on online courseware, an abundance of scientific libraries, and the fact that Python is one of the easiest programming languages to learn, means you don’t always have to be a PhD in Statistics to get the job done. Virtually every organization in the world is looking for Machine Learning/Deep Learning expertise, so this trend should help the supply side of this equation. The last analytics trend that is coming on strong in 2018 has to do with where data is analyzed. It will no longer be the exclusive domain of the cloud or large clusters of servers. The need to answer questions and make decisions more quickly is driving analytics of all types out to the Edge. Thanks to Moore’s Law and the need to eliminate latency, more and more edge gateway devices will be performing IFTTT and even Machine Learning predictions (with models trained in the cloud). There’s no shortage of important trends that are simplifying advanced analytics for organizations in 2018.

Clearly, 2018 is going to be a transformational year where properly-equipped decision-makers and leaders can shift their organization into the next gear to accelerate their digital transformation.

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares that a Digital Twin is a digital representation of a physical object -- at Hitachi we call these Asset Avatars. Asset Avatars are comprised of two components, an Avatar Type which defines the attributes and behaviors of a physical object and the other is the Avatar itself which collects and acts on sensor data. You can think of the Avatar Type as the asset's DNA and the Avatar itself as the brain.

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains what is preventing the $11 Trillion Internet of Things business from launching into the stratosphere. It needs to be easier to develop, deploy and use. It needs to work with existing machines and devices, not just the latest and greatest. Projects need to be geared toward getting quick wins rather than multi-year efforts to boil the ocean. The combined costs of all the IoT components must be lower to ensure an ROI for customers. Lastly, every component of an IoT solution must be secured from hackers or no one's going to deploy this technology.

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares his experiences from his participation in the creation of numerous Internet of Things (IoT), Mobile Device Management (MDM) and Mobile Enterprise Application Platforms (MEAP) over the course of his career. These software platforms share many valuable concepts and technologies that can help drive digital transformation when combined together.

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he shares that despite the great promise of IoT to improve business and society, many think it's being held back due to complexity and the associated lack of required skills to make it a success. Is it possible that the antidote to this complexity and skill shortage problem lies in the existing open standards and technologies that comprise the World Wide Web?

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains how you can streamline your processes and cut costs by putting your supply chain on autopilot. An IoT platform can make B2B connections to vendors and suppliers to automatically reorder products based on inventory levels and customer preferences so you never run out of stock and always deliver the products customers want.

Join Rob Tiffany, Hitachi Vantara's CTO for the Lumada IoT Platform, as he explains that when retail machines talk to each other directly or collaborate through edge gateways, customers are more likely to find what they're looking for. Why lose a sale due to a lack of inventory when a customer can be redirected to a nearby location where their product preferences can be met.